Precision estimates of longitudinal brain aging capture unexpected individual differences in one year.

Cluster scanning substantially reduces measurement error compared to single scans, improving precision of individualized brain aging estimates.

• The approach involves densely repeating rapid structural MRI scans within a session (cluster scanning) to reduce error through averaging.
• Three timepoints were assessed across one year, enabling longitudinal tracking of brain change.
• The improved precision reveals individual differences that would be undetectable with standard single-scan approaches.
• Precision improvements allowed detection of brain aging differences over the short interval of one year.

Cluster scanning detected expected differences in rates of brain aging between younger and older individuals within just one year.

• Age-related differences in brain change rates were detectable over a one-year interval using cluster scanning.
• These differences between younger and older individuals were previously undetectable over such short intervals due to measurement error.
• The study included multiple age groups to capture the expected trajectory of brain aging.

Cluster scanning detected differences in brain aging rates between cognitively unimpaired and cognitively impaired individuals within one year.

• Differences in brain change were observable between cognitively unimpaired and impaired individuals over the one-year study period.
• This finding demonstrates the clinical utility of cluster scanning for short-term detection of pathological brain change.
• The ability to distinguish impaired from unimpaired individuals in one year represents a significant improvement over standard longitudinal approaches.

Cognitively unimpaired older individuals showed marked heterogeneity in brain aging trajectories, including relative brain maintenance, unexpectedly rapid decline, and asymmetrical changes.

• Even within the cognitively unimpaired older group, individuals variably showed relative brain maintenance or unexpectedly rapid decline.
• Asymmetrical brain changes were also observed in cognitively unimpaired older individuals.
• These atypical brain aging trajectories were observed across multiple brain structures.
• The heterogeneous trajectories were verified in independent within-individual test-retest data, confirming their reliability.

Atypical brain aging trajectories identified through cluster scanning were verified in independent within-individual test-retest data.

• To validate the observed individual differences, the authors used independent within-individual test-retest data.
• Verification across independent data confirmed that the detected trajectories reflect true individual differences rather than measurement artifacts.
• Atypical trajectories were verified across multiple brain structures.

Cluster scanning promises to advance understanding of heterogeneity in brain aging by enabling better short-term tracking of individual variability in structural change.

• The method affords tracking of individual variability in structural brain change over short intervals.
• The approach addresses a fundamental challenge in longitudinal brain aging studies: measurement error over short intervals.
• The authors position cluster scanning as a tool for capturing the marked heterogeneity in brain aging trajectories across individuals.